--- license: apache-2.0 language: - de pipeline_tag: text-generation tags: - german - deutsch - simplification - vereinfachung --- # Model Card for Model ID We fine-tuned the [jphme/em_german_leo_mistral](https://huggingface.co/jphme/em_german_leo_mistral) with a set of ca. 2000 newspaper articles which have been simplified by the Austrian Press Agency. Our aim was to have a model which can simplify German-language text. ## Model Details ### Model Description - **Developed by:** Members of the [Public Interest AI research group](https://publicinterest.ai/), [HIIG Berlin](https://www.hiig.de/) - **Model type:** simplification model, text generation - **Language(s) (NLP):** German - **License:** Apache 2.0 - **Finetuned from model:** jphme/em_german_leo_mistral ### Model Sources - **Repository:** https://github.com/fhewett/simba - **Project website:** https://publicinterest.ai/tool/simba ## Uses ### Direct Use This model works best for simplifying German-language newspaper articles (news items, not commentaries or editorials). It may work for other types of texts. ### Downstream Use We have fine-tuned using only newspaper articles. We have not yet performed extensive out-of-domain testing, but believe that the model's capabilities could be improved by fine-tuning on more diverse data. Contact us if you have a dataset which you think could work (parallel texts, German standard & German simplified). ## Bias, Risks, and Limitations As with most text generation models, the model sometimes produces information that is incorrect. ### Recommendations Please check manually that your output text corresponds to the input text, as factual inconsistencies may have arisen. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data A sample of the data used to train our model can be found [here](https://github.com/fhewett/apa-rst/tree/main/original_texts). ### Training Procedure #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - **Training regime:** [More Information Needed] ## Evaluation ### Testing Data, Factors & Metrics #### Testing Data [More Information Needed] #### Factors [More Information Needed] #### Metrics [More Information Needed] ### Results [More Information Needed] #### Summary ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Model Card Contact simba -at- hiig.de